At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.
Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.
We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.
Job Description
Architecture & Platform Strategy
Define and evolve the target-state architecture for the self-serve data, AI, and agentic AI platform, aligned to enterprise strategy, data mesh principles, and regulatory requirements
Establish enterprise standards and reference architectures for data products, semantic layer services, AI/LLM gateways, agent orchestration, and API- and MCP-based data access
Architect the platform layers that let AI systems and agents find, trust, ask, and act on enterprise data — including data product interfaces, semantic context services, and governed write/action patterns
Define tiered certification and governance patterns that scale data product trust from registered assets to autonomous-grade, AI-ready products
Establish foundational patterns for retrieval, context enrichment, grounding, and tool exposure (RAG, semantic layer, MCP tool surfaces) to support agentic and real-time decisioning use cases
Engineering & Infrastructure
Lead engineering of scalable, secure platform infrastructure on AWS (S3, Lake Formation, Glue, EKS, Bedrock, IAM, networking) and Databricks (Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, Mosaic AI)
Engineer the agentic AI platform stack: agent runtimes, orchestration, agent identity and access management, action/write contracts, evaluation harnesses, and observability
Implement platform engineering best practices: infrastructure-as-code (Terraform), CI/CD, automated testing, environment promotion, and GxP/Part 11-compliant change management
Drive operational excellence across reliability, cost management (FinOps for data and AI workloads), observability, and incident response, grounded in SRE and Well-Architected practices
Ensure security, data protection, and access governance patterns (fine-grained entitlements, row/column-level controls, audit lineage) meet regulated-industry requirements
Delivery Leadership & Product Management
Contribute to the platform product roadmap: define outcomes, prioritize the backlog, and sequence capability delivery against enterprise AI adoption goals
Lead delivery across a team of vendor partners, holding the team to clear standards for quality, velocity, and operability
Drive build/buy/adopt decisions with rigor — vendor evaluation, kill criteria, and total-cost analysis — and integrate acquired capabilities into a coherent platform experience
Define and track platform health and adoption metrics (DORA, reliability SLOs, self-serve adoption, time-to-data-product) and report progress to senior leadership
Serve as a trusted advisor and technical leader: mentor engineers, run architecture reviews, and partner with business domains to identify and enable high-value data and AI use cases
Communicate architecture and trade-offs crisply to audiences from engineers to Director/VP. stakeholders, simplifying complexity without losing rigor
Basic Qualifications
10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture, including 3+ years leading engineering teams or major platform programs
Deep hands-on expertise with AWS data and AI services, including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform-based infrastructure automation
Strong production experience with Databricks: Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and workspace/governance administration at enterprise scale
Demonstrated experience designing or building agentic AI or LLM-powered systems: agent orchestration, RAG pipelines, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability
Proven ability to build resilient, scalable pipelines for high-volume batch and streaming data, with proficiency in SQL and Python (or Scala/Java)
Strong understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns
Experience designing secure, governed, production-grade cloud architectures, including fine-grained access control, lineage, and auditability
Track record of delivery leadership: roadmap ownership, backlog management, cross-functional coordination, and shipping platform capabilities that achieve measured adoption
Excellent communication skills with the ability to simplify complexity and influence senior decision-makers
Preferred Qualifications
Experience in biopharma, life sciences, or other heavily regulated domains, with working knowledge of GxP, 21 CFR Part 11, and computer system validation
Background in data mesh or federated data architectures, data product operating models, and domain enablement at enterprise scale
Experience with semantic layer technologies, knowledge graphs, metadata/catalog platforms, and data contract frameworks
Familiarity with FinOps for data and AI workloads, including cost attribution, chargeback/showback, and LLM token economics
Experience managing large vendor/partner ecosystems and running structured vendor evaluations with defined success and kill criteria
Product management experience or certification; familiarity with DORA metrics, SPACE framework, and platform-as-a-product operating models
AWS Professional (Solutions Architect or Data Analytics) and/or Databricks certifications
For additional benefits information, visit:
https://www.gilead.com/careers/compensation-benefits-and-wellbeing
* Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.
For jobs in the United States:
Gilead Sciences Inc. is committed to providing equal employment opportunities to all employees and applicants for employment, and is dedicated to fostering an inclusive work environment comprised of diverse perspectives, backgrounds, and experiences. Employment decisions regarding recruitment and selection will be made without discrimination based on race, color, religion, national origin, sex, age, sexual orientation, physical or mental disability, genetic information or characteristic, gender identity and expression, veteran status, or other non-job related characteristics or other prohibited grounds specified in applicable federal, state and local laws. In order to ensure reasonable accommodation for individuals protected by Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veterans' Readjustment Act of 1974, and Title I of the Americans with Disabilities Act of 1990, applicants who require accommodation in the job application process may contact [email protected] for assistance.
For more information about equal employment opportunity protections, please view the 'Know Your Rights' poster.
NOTICE: EMPLOYEE POLYGRAPH PROTECTION ACT
YOUR RIGHTS UNDER THE FAMILY AND MEDICAL LEAVE ACT
Gilead Sciences will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, (c) consistent with the legal duty to furnish information; or (d) otherwise protected by law.
Our environment respects individual differences and recognizes each employee as an integral member of our company. Our workforce reflects these values and celebrates the individuals who make up our growing team.
Gilead provides a work environment free of harassment and prohibited conduct. We promote and support individual differences and diversity of thoughts and opinion.
For Current Gilead Employees and Contractors:
Please apply via the Internal Career Opportunities portal in Workday.
Skills Required
- 10+ years in platform engineering, data engineering, or enterprise data/AI platform architecture
- 3+ years leading engineering teams or major platform programs
- Hands-on expertise with AWS data and AI services including S3, Lake Formation, Glue, EKS, Bedrock, Kinesis/MSK, IAM, and Terraform
- Production experience with Databricks, including Unity Catalog, Delta Lake, Delta Live Tables, Databricks SQL, MLflow, and enterprise workspace governance
- Experience designing or building agentic AI or LLM-powered systems, including orchestration, RAG, LLM gateways, tool/function calling, MCP or comparable protocols, and AI evaluation/observability
- Experience building resilient, scalable batch and streaming data pipelines; proficiency in SQL and Python, Scala, or Java
- Understanding of distributed systems, event-driven architecture, workflow orchestration, and API-first integration patterns
- Experience designing secure, governed, production-grade cloud architectures with fine-grained access control, lineage, and auditability
- Track record of roadmap ownership, backlog management, cross-functional coordination, and delivering adopted platform capabilities
- Excellent communication skills and ability to influence senior decision-makers
- Experience in biopharma, life sciences, or heavily regulated domains, including GxP, 21 CFR Part 11, and computer system validation
- Experience with data mesh or federated data architectures, data products, and domain enablement
- Experience with semantic layers, knowledge graphs, metadata/catalog platforms, and data contract frameworks
- Familiarity with FinOps for data and AI workloads, cost attribution, chargeback/showback, and LLM token economics
- Experience managing vendor ecosystems and conducting structured vendor evaluations
- Product management experience or certification; familiarity with DORA, SPACE, and platform-as-a-product practices
- AWS Professional or Databricks certifications
Gilead Sciences Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Gilead Sciences and has not been reviewed or approved by Gilead Sciences.
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Fair & Transparent Compensation — Pay is considered competitive and fair relative to roles, frequently cited as a standout strength. Feedback suggests compensation compares well within biotech and is a notable reason employees feel valued.
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Equity Value & Accessibility — Stock awards and an employee stock purchase program are consistently described as meaningful parts of total compensation. Equity components are seen as accessible and enhance long‑term wealth building.
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Retirement Support — A strong company 401(k) match with immediate vesting is often singled out as a differentiator. This support is perceived to significantly boost long‑term financial security.
Gilead Sciences Insights
What We Do
The way we see it, the impossible is not impossible. It’s simply what hasn’t been achieved yet. For more than 30 years, we’ve pursued it, chased it down, tackled it for answers and surrounded it for a way in. We have worked tirelessly to bring forward medicines for life-threatening diseases. Creating Possible drives everything we do. It’s evident in our mission and core values. This is how we built a culture of excellence that is fueled by a passion for improving lives of people around the world. For us, nothing is impossible – because of the people we work with, the communities we stand with and the partners we push forward with. Our ~12,000 employees band together through science, grit, compassion and courage to prove the impossible wrong. At Gilead, the tangible results of your contributions are evident. Where every individual matters. Where all employees can enhance their skills through ongoing development. And where we start every day with one question: “What’s next?” Social Media Guidelines: https://gilead.inc/3t1m7d5







